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Policy, sovereignty & data spaces

From Europe’s data ambition to operational sovereignty.

Europe wants to make more high-quality data available for innovation, public value and AI—without organisations and data rights holders losing control. Data spaces make that balance operational.

01

2020 · The foundation

European Data Strategy

The strategy introduced the ambition for a European single market for data: data should be usable across the EU and across sectors while respecting European rules and values.

Shared rules

Reduce technical, legal and organisational barriers to the use of data.

Common data spaces

Develop shared infrastructure and governance for strategic European domains.

Retain control

Allow data holders to determine under which conditions their data becomes available.

Read the official European policy context
02

2025 · The next phase

Data Union Strategy

The Data Union Strategy builds on that foundation and connects it more directly to AI, competitiveness and strategic resilience.

Data for AI

Improve access to high-quality data and connect data spaces with AI ecosystems.

Simpler rules

Make the European data acquis easier to understand and apply.

Data sovereignty

Strengthen Europe’s ability to govern data, infrastructure and dependencies according to its interests.

Read the official Data Union Strategy

InformationGrid perspective

What this means now.

This is our translation of Europe’s direction into design principles for organisations and data ecosystems—not a separate EU policy programme.

Make control and data rights explicit

Use verifiable access and usage conditions

Use open interfaces and avoid unnecessary dependencies

Organise trust and evidence across organisational boundaries

Sovereignty is not isolation

It means being able to collaborate deliberately while retaining control over data, conditions, technology choices and continuity.

From policy to practice

A dataspace makes these ambitions operational.

Shared governance and standards connect autonomous participants while data remains as close to its source as possible and conditions are applied explicitly.